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Project | STREAMLINE

Duration:
Streamlined Analysis of Data at Rest and Data in Motion

Streamlined Analysis of Data at Rest and Data in Motion

Together with four leading European data economy enterprises as well as world-renown scientists and innovators DFKI will work in project STREAMLINE to meet modern day requirements of European online media businesses. Partners SICS, SZTAKI, PT, NMusic, IMR, and Rovio will jointly develop a analytics framework drawing on multi-source data originating from online media consumption, online games, telecommunication services, and multilingual web content.

State-of-the-art technologies only insufficiently handle use-cases such as targeted real-time services, customer retention, and customer profiling. System latencies arise due to a lack of appropriate data stream-oriented analytics tools supporting analysis of both data-at-rest and data-in-motion, while human latencies are due to the heterogeneity in tools which must be tediously glued together. The resulting solutions have reduced efficiency and effectiveness while increasing complexity, cost, and burden.

Project STREAMLINE will lower the big data skills barrier, thus broadening the reach of data analytics tools to SMEs in a wide range of market sectors including healthcare, manufacturing, and transportation. As an open-source technological enabler for European companies to build innovative, contextualized, multilingual data products and services, it will advance European leadership in big data technologies and the data economy transformation.

During the course of the project, DFKI will coordinate scientific and technical activities among its partners and perform technical research and development. The project will benefit from using Apache Flink as a well-established basis for developing a highly scalable, high-throughput real-time stream mining platform.

This project has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No 688191.

Partners

SICS Swedish ICT, MTA SZTAKI, PT Portugal, NMusic, IMR, Rovio

Publications about the project

  1. AStream: Ad-hoc Shared Stream Processing

    Tilmann Rabl Jeyhun Karimov; Tilmann Rabl; Volker Markl

    In: SIGMOD '19: Proceedings of the 2019 International Conference on Management of Data. ACM SIGMOD International Conference on Management of Data (SIGMOD-2019), June 30 - July 5, Amsterdam, Netherlands, Pages 607-622, ISBN 978-1-4503-5643-5, ACM, New York, NY, 6/2019.
  2. Continuous Deployment of Machine Learning Pipelines

    Behrouz Derakhshan; Alireza Rezaei Mahdiraji; Tilmann Rabl; Volker Markl

    In: International Conference on Extending Database Technology. International Conference on Extending Database Technology (EDBT-2019), March 25-29, Lisbon, Portugal, ISBN 978-3-89318-081-3, OpenProceedings, 2019.

Sponsors

EU - European Union

688191

EU - European Union